1、 List转Numpy

aList = [1,2,3,4,5]
bList = [1,3,5,7,9]
aList+bList

[1, 2, 3, 4, 5, 1, 3, 5, 7, 9]

import numpy as np
aArray = np.array(aList)
bArray = np.array(bList)

aArray+bArray

array([ 2,  5,  8, 11, 14])

2、 Numpy转Series

import pandas as pd
aSeries = pd.Series(aArray, index=pd.date_range("20180101",periods=len(aArray), freq="D"))
bSeries = pd.Series(bArray, index=pd.date_range("20180101",periods=len(bArray), freq="D"))

cSeries = aSeries+bSeries
dSeries = aSeries*bSeries

3、 Series转DataFrame

abDF = pd.DataFrame({'a': aSeries, 'b':bSeries})

print(abDF)

            a  b
2018-01-01  1  1
2018-01-02  2  3
2018-01-03  3  5
2018-01-04  4  7
2018-01-05  5  9

print(pd.concat([aSeries, bSeries], axis=1, keys=['a','b']))

            a  b
2018-01-01  1  1
2018-01-02  2  3
2018-01-03  3  5
2018-01-04  4  7
2018-01-05  5  9

cdDF = pd.DataFrame({'a': cSeries, 'b':dSeries})

4、 DataFrame转Panel

abcdPN = pd.Panel({'abDF': abDF, 'cdDF': cdDF})

print(abcdPN.transpose(2,1,0).to_frame(False))

                   a   b
major      minor        
2018-01-01 abDF    1   1
           cdDF    2   1
2018-01-02 abDF    2   3
           cdDF    5   6
2018-01-03 abDF    3   5
           cdDF    8  15
2018-01-04 abDF    4   7
           cdDF   11  28
2018-01-05 abDF    5   9
           cdDF   14  45

5、 iteritem()

计算每一列的加总

{item: value.sum() for item, value in abDF.iteritems()}

{'a': 15, 'b': 25}

6、 iterrow()

计算每一行的加总

{index: value.sum() for index, value in abDF.iterrows()}

{Timestamp('2018-01-01 00:00:00', freq='D'): 2,
 Timestamp('2018-01-02 00:00:00', freq='D'): 5,
 Timestamp('2018-01-03 00:00:00', freq='D'): 8,
 Timestamp('2018-01-04 00:00:00', freq='D'): 11,
 Timestamp('2018-01-05 00:00:00', freq='D'): 14}